{"as_of":"2026-08-10T08:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:544cba2e4132f965a424e1d793c849697731a6c58f3d31a203152c7aefb1ed9d","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T23:24:39.284094Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.18474/citation-record","integrity":"/paper/2501.18474/integrity","json":"/paper/2501.18474/citation-record.json","paper":"/paper/2501.18474"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.691629Z","title":"Long-term outcome after stroke: does dysphagia matter?","venue":null,"work_id":"2115fb5a-a998-4b24-bc04-4a5528e68256","year":2007},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.161947Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:d1dbd8eea5118bfab0cd8e4463f3f0a506c66418c26d57e8f49dba07a2d514d2","observation_id":"f2cccac5-cc09-4d04-a360-6dbec2c81d0a","resolution":{"observed_at":"2026-08-09T23:24:39.695976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.680229Z","title":"Dysphagia: A geriatric giant?","venue":null,"work_id":"3703e67c-f04d-4767-916b-20fd5c95997b","year":2016},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.166735Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:372640e1d78a7ddb42ebfb305827965d93adf1ed09eb2c75c59e93d619529a6a","observation_id":"c4afa2e1-16c6-4c9b-8b2b-e58acea22103","resolution":{"observed_at":"2026-08-09T23:24:39.684126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.668269Z","title":"The natural history of dysphagia following a stroke,","venue":null,"work_id":"0ee7add6-43a7-431e-8c9d-480a51db2137","year":1997},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.170808Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:53f8069887f54cdca75937c897f96461ce80d9f2c661ca102a24f4c9fa65f421","observation_id":"c45b66b6-fd20-4368-a042-1e50e0393c3d","resolution":{"observed_at":"2026-08-09T23:24:39.672429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.657161Z","title":"Early assessments of dysphagia and aspiration risk in acute stroke patients,","venue":null,"work_id":"24aa109f-6c78-4c85-b428-28ae95f3010e","year":2003},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.175297Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:a3ed344e80cc78ff42ddd412155cb708e1e13c36a2c5c9188a863e68a5fae8d4","observation_id":"9f71ed0c-d495-4d5c-b0df-84924f807a6c","resolution":{"observed_at":"2026-08-09T23:24:39.660829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.646258Z","title":"Segment anything,","venue":null,"work_id":"334a434d-685e-4a23-8959-2012c4419bc0","year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.179419Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:c248821a6253ea85c4f5275a7bf71ccc6febab93a91e29647e00f8fffc81deeb","observation_id":"c0c87500-0f69-48d9-9ba7-20c1d014de49","resolution":{"observed_at":"2026-08-09T23:24:39.649873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-09T23:24:39.183549Z","title":"Sam 2: Segment anything in images and videos,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.183549Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:a62f3f7777a315729858ed3865ef65f30b3285f12655815fc53b11e30d87a176","observation_id":"08f59c59-8db7-40b1-80fc-5f0b85010954","resolution":{"observed_at":"2026-08-09T23:24:39.183549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12306","last_updated":"2024-04-01T16:18:16Z","snapshot_observed_at":"2026-07-06T15:19:28.033750Z","submitted_at":"2023-04-24T17:56:12Z","title":"Segment Anything in Medical Images","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12306","snapshot_observed_at":"2026-08-09T23:24:39.188724Z","title":"Segment anything in medical images,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.188724Z"},"links":{"cited_paper":"/paper/2304.12306","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:e7f58a17fdc1e65ec70d30e541ede93ccc9d60704d28faddcc38fc3763b1190d","observation_id":"a0e2d4aa-cb96-453d-a16b-3a4d9643f52b","resolution":{"observed_at":"2026-08-09T23:24:39.188724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00874","last_updated":"2024-12-04T23:51:25Z","snapshot_observed_at":"2026-08-04T09:38:10.661882Z","submitted_at":"2024-08-01T18:49:45Z","title":"Medical SAM 2: Segment medical images as video via Segment Anything Model 2","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00874","snapshot_observed_at":"2026-08-09T23:24:39.193018Z","title":"Medical sam 2: Segment medical images as video via segment anything model 2,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.193018Z"},"links":{"cited_paper":"/paper/2408.00874","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:6436f3054d8e3f0ead9ad593fa94cedd6ed2f884e91751188cfd9b98d889858b","observation_id":"75ba1e71-c53f-415c-9cde-bd5b6c9cb21b","resolution":{"observed_at":"2026-08-09T23:24:39.193018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12620","last_updated":"2023-12-29T03:40:59Z","snapshot_observed_at":"2026-07-06T15:19:39.223171Z","submitted_at":"2023-04-25T07:34:22Z","title":"Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12620","snapshot_observed_at":"2026-08-09T23:24:39.197692Z","title":"Medical sam adapter: Adapting segment anything model for medical image segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.197692Z"},"links":{"cited_paper":"/paper/2304.12620","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:dd75b06101664eeb9a9f00f972b12a5504157a552c1935958364e305c9c9e914","observation_id":"add18804-9cd4-4c99-a062-9b4147aabd05","resolution":{"observed_at":"2026-08-09T23:24:39.197692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.634901Z","title":"Segment anything model for medical image analysis: an experimental study,","venue":null,"work_id":"06c91c9e-3515-4147-ae03-551dc6045a91","year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.201909Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:f041e3397adbf2a77bce47a0227eb5045c5767c85d4787b2ace412b082b4f5c2","observation_id":"6d68aadc-434b-40a8-9e32-d3e79b37fc77","resolution":{"observed_at":"2026-08-09T23:24:39.638651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.07522","last_updated":"2022-09-15T17:59:34Z","snapshot_observed_at":"2026-08-10T04:50:43.350850Z","submitted_at":"2022-09-15T17:59:34Z","title":"Test-Time Training with Masked Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.07522","snapshot_observed_at":"2026-08-09T23:24:39.205973Z","title":"Test-time training with masked autoencoders,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.205973Z"},"links":{"cited_paper":"/paper/2209.07522","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:1bce6215feb91f2b5ac2f5ad27f43ad74975829eddbb686e886fc13e6059d68b","observation_id":"731a20c1-1f67-4d74-b58b-9790c5463de4","resolution":{"observed_at":"2026-08-09T23:24:39.205973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.623620Z","title":"Ttt++: When does self-supervised test-time training fail or thrive?","venue":null,"work_id":"73b4c44d-c3ab-48fb-9e8d-6666685700f4","year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.210257Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:28604b06be9446393b82a8531905f0dcd426be07109ef8f23db07434bb382fe2","observation_id":"1dbf8133-18aa-42da-b3fe-d63e4214a679","resolution":{"observed_at":"2026-08-09T23:24:39.627521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.611617Z","title":"Depth- aware test-time training for zero-shot video object segmentation,","venue":null,"work_id":"3132b338-f549-4a0e-aba7-1c55df6f49cb","year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.213940Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:7219ffca0b82a877ae83cbc03fdf21fbbeaa1a0242cf80ea740f20e9a4ee2c21","observation_id":"cdb177d4-a123-47dc-a797-77a3ac369dfd","resolution":{"observed_at":"2026-08-09T23:24:39.615825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.599562Z","title":"Test-time adaptable neural networks for robust medical image segmentation,","venue":null,"work_id":"deca01c0-ac97-41df-9680-03b2eb8dda7e","year":2020},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.217702Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:383c9d5f079b651e2b08781d6e7f79fd4fc8897d7bb9bbe0210a0026b31f4e85","observation_id":"64cf7667-eb03-4a7e-831d-d84a90c1028c","resolution":{"observed_at":"2026-08-09T23:24:39.603798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.584986Z","title":"Test- time training with self-supervision for generalization under distribution shifts,","venue":null,"work_id":"c4a58fa9-35f4-43af-9c39-ac85fb6ab97f","year":2019},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.221536Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:a0a1713af5a931d4609b1ba5348c3c0398a4b33861a7163a226e00831c4721a6","observation_id":"540cdd80-aa94-40a0-bdcc-98bb3e52f729","resolution":{"observed_at":"2026-08-09T23:24:39.590825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.00989","last_updated":"2023-06-01T17:59:58Z","snapshot_observed_at":"2026-08-09T06:04:31.284029Z","submitted_at":"2023-06-01T17:59:58Z","title":"Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.00989","snapshot_observed_at":"2026-08-09T23:24:39.225259Z","title":"Hiera: A hierarchical vision transformer without the bells-and-whistles,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.225259Z"},"links":{"cited_paper":"/paper/2306.00989","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:e4dfd33f832e46812bf18a31734a571485c6c3fc5aa57ee7527d2c8a2add541d","observation_id":"a3477aa8-b805-4aa1-8f1a-eee301e6885c","resolution":{"observed_at":"2026-08-09T23:24:39.225259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03322","last_updated":"2024-08-06T17:58:18Z","snapshot_observed_at":"2026-08-04T09:23:08.214972Z","submitted_at":"2024-08-06T17:58:18Z","title":"Segment Anything in Medical Images and Videos: Benchmark and Deployment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03322","snapshot_observed_at":"2026-08-09T23:24:39.229349Z","title":"Segment anything in medical images and videos: Benchmark and deployment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.229349Z"},"links":{"cited_paper":"/paper/2408.03322","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:bdf578bdfe3f8e7c333a16ba7af720bfd6eacd131dcbd84a25b893b27590291b","observation_id":"a9ae7491-9066-4ca0-9a70-3cbaf353dafe","resolution":{"observed_at":"2026-08-09T23:24:39.229349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.572778Z","title":"Automated bolus detection in videofluoroscopic images of swallowing using mask- rcnn,","venue":null,"work_id":"bef15cc6-6880-447f-96db-f6e6fbd2dd07","year":2020},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.232736Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:defd56498612a7072ddf04a423a1bcc56a294e7c6d67f3b4dc87ebabaef31a84","observation_id":"16000dbb-c1ca-44dc-8c5f-0cab6f29365b","resolution":{"observed_at":"2026-08-09T23:24:39.577223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.560507Z","title":"Automated pharyngeal phase detection and bolus localization in videofluoroscopic swallowing study: Killing two birds with one stone?","venue":null,"work_id":"73badd65-fc81-4c35-90b7-1a92f96011aa","year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.235722Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:8604729b15a5bb091e0c4a11092598161793b2aebcc525c0fb9ae401d56d8cf7","observation_id":"2c4c9ff7-bcb0-48af-9904-0e09f3b74fe7","resolution":{"observed_at":"2026-08-09T23:24:39.565126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.544867Z","title":"Deep learning-based auto-segmentation and evaluation of vallecular residue in videofluo- roscopy,","venue":null,"work_id":"4c38882c-cf95-4735-bfee-964243320fe0","year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.239709Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:be49dcc83438bc49a8d282bf7d90d382605c50e90680901f38dd0e40021dd630","observation_id":"76a1d375-3292-434e-a7e7-55d90d648c24","resolution":{"observed_at":"2026-08-09T23:24:39.549552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.531402Z","title":"Peci-net: Bolus segmentation from video fluo- roscopic swallowing study images using preprocessing ensemble and cascaded inference,","venue":null,"work_id":"864dd759-98c4-4b30-b5fa-01c9919024ee","year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.242980Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:f9cad3472315a6ec758d5e7635f270bc861cd0e8ef24d8a0de99ea089d71f206","observation_id":"bef1fe51-8c0b-4b24-9a14-c4c5965ab5a0","resolution":{"observed_at":"2026-08-09T23:24:39.535728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.517673Z","title":"Tent: Fully test-time adaptation by entropy minimization,","venue":null,"work_id":"283ec640-6d4e-4f7a-baa1-6db3efd5fb83","year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.246071Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:9d1b01909b83c615c53b6a34000710c81adf64eadf3b93087474ff7123e9d060","observation_id":"a7835b5c-9eea-4e6c-bffe-d1d98d66f299","resolution":{"observed_at":"2026-08-09T23:24:39.522080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01573","last_updated":"2024-10-02T14:11:26Z","snapshot_observed_at":"2026-08-07T17:51:57.615786Z","submitted_at":"2024-10-02T14:11:26Z","title":"PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":"2410.01573","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.01573","snapshot_observed_at":"2026-08-09T23:24:39.364093Z","title":"PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation","venue":"cs.CV","work_id":"6f4e68d0-2c61-4837-ae15-8f6123161dae","year":2024},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.249267Z"},"links":{"cited_paper":"/paper/2410.01573","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:e80bf48e0c66656a64fcb0f49e432318469ca0dbab6c133d5eb54aee88efdaf7","observation_id":"d4e2be78-9bb5-4b00-ac82-d884578b369c","resolution":{"observed_at":"2026-08-09T23:24:39.370591Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-06T11:05:16.105361Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-09T23:24:39.253199Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.253199Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:1557c18531b1a4103e149890591befe24bd20172ba17c1b6c66ab9e7d1485dcd","observation_id":"f51cb633-6a93-464f-9059-e1fe1e34aa0f","resolution":{"observed_at":"2026-08-09T23:24:39.253199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.504057Z","title":"Stoyanov, Z","venue":null,"work_id":"d78cf198-6249-448e-b053-9a9d155c9bc0","year":2018},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.257277Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:c27ec4a7bbb83d361ae7c2c3eaf99e3ec7cc50829ae23218c1672170eb3bece6","observation_id":"738d24a3-b7d6-4660-bb2a-f79851a21e43","resolution":{"observed_at":"2026-08-09T23:24:39.508459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.492160Z","title":"Road extraction by deep residual u-net,","venue":null,"work_id":"f878a7c5-5287-4e9f-a853-6a0fe02714d6","year":2017},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.260919Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:49b22000f0f7f43107a5b15ac6c9385ed88196b0dd0bc18982a58f62458bdd08","observation_id":"8fbc0f03-1c9c-45c6-83dd-20f4799f7a0d","resolution":{"observed_at":"2026-08-09T23:24:39.496018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03999","last_updated":"2018-05-20T23:33:30Z","snapshot_observed_at":"2026-07-06T06:32:53.966022Z","submitted_at":"2018-04-11T14:13:03Z","title":"Attention U-Net: Learning Where to Look for the Pancreas","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03999","snapshot_observed_at":"2026-08-09T23:24:39.264557Z","title":"Attention u-net: Learning where to look for the pancreas,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.264557Z"},"links":{"cited_paper":"/paper/1804.03999","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:c032b663655aca686cf18e1de1542a803f75819ab3e6fa2f754728b98ece9a8f","observation_id":"71ad958e-00a5-45f6-8bfe-10461a72f5e3","resolution":{"observed_at":"2026-08-09T23:24:39.264557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04306","last_updated":"2021-02-08T16:10:50Z","snapshot_observed_at":"2026-08-10T02:39:10.770770Z","submitted_at":"2021-02-08T16:10:50Z","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.04306","snapshot_observed_at":"2026-08-09T23:24:39.268767Z","title":"Transunet: Transformers make strong encoders for medical image segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.268767Z"},"links":{"cited_paper":"/paper/2102.04306","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:ffb070fee08d2648ec97e5e41aed478763a2b68a0cc81449ef6c1ab60cb4565e","observation_id":"2faafe61-6a50-4d63-97a8-757bbf05f73a","resolution":{"observed_at":"2026-08-09T23:24:39.268767Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.480251Z","title":"Video-transunet: Temporally blended vision transformer for ct vfss instance segmentation,","venue":null,"work_id":"0ab0ab51-fc88-4440-bd20-bec032b720cc","year":2022},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.272517Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:bafec2846a25412b27fe531790d6ef5c748c86861d2ca930793747844fdf90df","observation_id":"c717c1c6-a18d-4b44-bb5f-5d47ba67dd75","resolution":{"observed_at":"2026-08-09T23:24:39.484168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.05537","last_updated":"2021-05-12T09:30:26Z","snapshot_observed_at":"2026-07-06T11:08:42.400145Z","submitted_at":"2021-05-12T09:30:26Z","title":"Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.05537","snapshot_observed_at":"2026-08-09T23:24:39.276143Z","title":"Swin-unet: Unet-like pure transformer for medical image segmenta- tion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.276143Z"},"links":{"cited_paper":"/paper/2105.05537","citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:a43e00049af647548310adf8005018e1aa6b876905fdf9212291dc6590b204fb","observation_id":"16951f5b-2356-4322-8425-a1d21a985fdb","resolution":{"observed_at":"2026-08-09T23:24:39.276143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.469197Z","title":"Video-swinunet: Spatio-temporal deep learning frame- work for vfss instance segmentation,","venue":null,"work_id":"a6d11c7b-39c1-4118-b9d7-ce29983ff29b","year":2023},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.280295Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:1a26afab1eb54bb9a53bdf3f4fa4e5261d8ba511a7c43132efe5621130909850","observation_id":"bf1f5f9d-647a-43bc-9ed9-eec991725a9a","resolution":{"observed_at":"2026-08-09T23:24:39.472995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T23:24:39.456980Z","title":"Simultaneous truth and performance level estimation (staple): an algorithm for the validation of image segmentation,","venue":null,"work_id":"dbe3f6a3-39fb-4116-b0af-75566aefd70e","year":2004},"citing_paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T23:24:39.284094Z"},"links":{"citing_paper":"/paper/2501.18474"},"observation_digest":"sha256:0f386da7cbdf531944fdffffc508589952dd33f2a6ed0eaca9a26167bb12e572","observation_id":"0af3ca3f-1725-4237-bbc2-45abe3a89fbf","resolution":{"observed_at":"2026-08-09T23:24:39.461177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.18474","last_updated":"2025-01-30T16:48:02Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T08:02:53.622594Z","submitted_at":"2025-01-30T16:48:02Z","title":"Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":1,"verified_fuzzy":20},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2501.18474."}